Biology subjects

song, j.

Publications and source records attributed to song, j..

5 recordsLinked to original sources

bioRxiv2026

Spaceland: Histology-Guided Reconstruction of High-Resolution Whole-Organ 3D Molecular Atlases from Sparse Spatial Transcriptomics

Reconstructing whole organs in three-dimensional molecular detail is a key step toward building virtual organs for modeling tissue organization, disease progression and drug perturbation responses. However, high-resolution whole-organ spatial transcriptomic profiling remains impractical, forcing a trade-off between reconstruction fidelity and sampling density. Here, we introduce Spaceland, a morphology-guided framework that reconstructs continuous, high-resolution 3D molecular landscapes from sparsely sampled spatial transcriptomic sections and serial H&E histology. Spaceland formulates this task as learning continuous gene-expression fields within a morphology-informed histological space. It constructs a dense 3D morphological scaffold by optical-flow interpolation of foundation model-derived H&E representations and decodes sparse spot-level transcriptomic measurements onto an 8 m histology-aligned grid. Across mouse olfactory bulb, mouse hemibrain and spatiotemporal planarian regeneration, Spaceland generalized across platforms, tissue scales and biological contexts. In mouse benchmarks, Spaceland bridged 400 m molecular gaps, resolved sub-spot organization, outperformed ST-based interpolation and 2D H&E-based prediction methods, and remained robust with 160-320 m H&E intervals. In planarian regeneration, it enabled time-resolved whole-organism analysis from only four Visium sections per stage, revealing dynamic neoblast-neural spatial remodeling. Together, Spaceland shifts 3D molecular atlas construction from exhaustive experimental sampling toward data-driven virtual tissue and organ modeling, providing a scalable route to whole-organ molecular reconstruction.

bioinformatics↗

bioRxiv2024

Nephrectomy and high-salt diet inducing pulmonary hypertension and kidney damage by increasing Ang II concentration in rats

BackgroundPulmonary hypertension (PH) is a common complication in patients with chronic kidney disease (CKD), affecting prognosis. However, the pathogenesis is not clear, and the lack of a stable animal model is a significant factor. MethodsIn this study, a rat model of chronic kidney disease with pulmonary hypertension (CKD-PH) was developed through 5/6 nephrectomy combined with a high-salt diet. The models hemodynamics and pathological changes in multiple organs were dynamically assessed. Lung tissues and serum were collected from the model rats to measure the expression of ACE2, the expression levels of vascular active components related to the renin-angiotensin-aldosterone system (RAAS), and changes in the serum metabolic profile of the model. ResultsAfter 14 weeks post-surgery, the CKD-PH rat model exhibited significant changes in hemodynamic parameters indicative of pulmonary arterial hypertension, along with alterations such as right ventricular hypertrophy. However, no evidence of pulmonary vascular remodeling was observed. An imbalance in the renin-angiotensin-aldosterone system was identified in the CKD-PH rat models. Downregulation of ACE2 expression was observed in pulmonary tissues. The serum metabolic profile of the CKD-PH rat models showed distinct differences compared to the sham surgery group. ConclusionsThe development of pulmonary arterial hypertension in CKD-PH rats may be primarily attributed to the disruption of the renin-angiotensin-aldosterone system (RAAS), coupled with a decrease in ACE2 expression in pulmonary vascular endothelial tissues and metabolic disturbances.

pathology↗

bioRxiv2023

Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes

High-throughput single-cell RNA sequencing (scRNA-seq) is recognized as a powerful technology for disentangling the heterogeneity of cellular states. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and for samples with low RNA-content. Herein, to address these challenges, we developed Well-Paired-Seq2 (WPS2) based on size-exclusion and locally quasi-static hydrodynamic principles to realize high efficiency of cell utilization, single cell/bead pairing, and cell-free RNA removal. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts. With an average of [~]20,000 reads per cell, WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. Using WPS2, we overcame the Poisson limit for the capture of both cells and beads and accurately characterized transcriptomes of low RNA-content single cells and nuclei with high sensitivity. WPS2 was further applied to comprehensively profile transcriptomes from frozen clinical samples. We found that clear cell renal cell carcinoma (ccRCC) has a complex microenvironment, and that chromophobe renal cell carcinoma (chRCC) exhibits abundant copy number variations (CNVs). In addition, metanephric adenoma (MA) was characterized at single-cell level for the first time and some potentially specific markers were revealed. With the advantages of high sensitivity, high throughput, and high fidelity, we anticipate that WPS2 will be broadly applicable in basic and clinical research.

genetics↗

bioRxiv2022

IDOL deficiency inhibits cholesterol-rich diet-induced atherosclerosis in rabbits

BACKGROUNDThe E3 ubiquitin ligase IDOL (Inducible Degrader of the LDL-Receptor) contributes to regulation of cholesterol metabolism through degradation of LDLR, VLDLR and ApoER2. Human genetic studies support the hypothesis that IDOL could serve as a target for the treatment of dyslipidemia. However, species-specific differences in overall lipid metabolism and IDOL regulation require new preclinical models to realize its therapeutic potential. We leveraged the advantages afforded by the rabbit model to address those limitations and generated a novel rabbit IDOL knockout, which we characterized in the context of atherosclerosis. METHODSIDOL-/- rabbits were generated by CRISPR/Cas9 technology. IDOL-/- and wildtype littermates, on standard (SD) and atherogenic high-cholesterol diets (HCDs) were compared through assessment of lipid and lipoprotein profiles, triglyceride clearance, lipoprotein lipase (LPL) activity, liver pathology, atherosclerosis development, and fecal cholesterol, with bile acid contents assessed by mass spectrometry. ResultsHepatic IDOL expression was increased in response to hypercholesterolemia and hypertriglyceridemia induced by HCD. On SD, loss of IDOL increased LDLR stability with reduced total cholesterol in plasma. On HCD, IDOL-/- rabbits showed simultaneous and remarkable reduction in hypercholesterolemia and hypertriglyceridemia associated with enhanced lipid clearance and LPL activity as well as increased bile acid excretion in feces. IDOL-/- rabbits presented markedly reduced HCD-induced atherosclerosis in the aorta and left coronary artery, without enhanced liver steatosis. CONCLUSIONSLoss of IDOL in rabbits recapitulates human genetic findings, thus setting the stage to accelerate preclinical studies towards development of strategies targeting IDOL for the treatment of atherosclerotic cardiovascular disease.

physiology↗

bioRxiv2020

A Reference Feature based method for Quantification and Identification of LC-MS based untargeted metabolomics

Batch inconsistency is a major problem when applying LC-MS based untargeted metabolomics in real-time analysis situation such as clinical diagnosis or health monitoring. And inefficiency of collecting MS2 is a major problem for metabolite identification. Here, we developed a reference-feature based quantification and identification strategy (RFQI). In RFQI, samples are individually profiled using a pre-fixed reference feature table. Quantification results show that RFQI improves features overlap rate and reduce variance across batches significantly in real-time-analysis mode, and can find more than 4-fold numbers of features. Besides, RFQI collects MS2 from consecutive increasing samples for metabolite identification of pre-fixed features, thus it can effectively compensate for the poor efficiency of MS2 collection in data-dependent acquisition mode. In summary, RFQI can make full advantage of consecutive increasing samples in real-time analysis situation, both for quantification and identification.

bioinformatics↗